/** Calculates the Food Made+Used data sets. */
private void calculateFoodMadeUsedDataSets() {
// Food Made+Used is showing 2 player stats at once: Food Made and Food Used
// First calculate FOOD_USED data set...
calculateDataSets(Stat.FOOD_USED);
// ...and clone it because we'll need it in a moment
final List<Chart<LineChartDataSet>> clonedChartList = new ArrayList<>(chartList.size());
for (final Chart<LineChartDataSet> chart : chartList) {
final Chart<LineChartDataSet> clonedChart = createChart();
for (final DataModel<LineChartDataSet> model : chart.getDataModelList()) {
final DataModel<LineChartDataSet> clonedModel =
new DataModel<>(model.getTitle(), model.getColor());
for (final LineChartDataSet dataSet : model.getDataSetList()) {
// Use brighter color as this will be the 2nd dataset
final Color color = ((User) model.getUserobObject()).getPlayerColor().brighterColor;
clonedModel.addDataSet(
new LineChartDataSet(
color, dataSet.getStroke(), dataSet.getLoops(), dataSet.getValues()));
}
clonedChart.addModel(clonedModel);
}
clonedChartList.add(clonedChart);
}
// Cloning done, let's roll on to calculating the FOOD_MADE data set...
calculateDataSets(Stat.FOOD_MADE);
// And the final step: "merge" the 2 data sets into one, simply add the datasets...
for (int chartIdx = 0; chartIdx < chartList.size(); chartIdx++) {
final Chart<LineChartDataSet> chart = chartList.get(chartIdx);
final Chart<LineChartDataSet> clonedChart = clonedChartList.get(chartIdx);
for (int modelIdx = 0; modelIdx < chart.getDataModelList().size(); modelIdx++) {
final DataModel<LineChartDataSet> model = chart.getDataModelList().get(modelIdx);
final DataModel<LineChartDataSet> clonedModel =
clonedChart.getDataModelList().get(modelIdx);
model.getDataSetList().addAll(clonedModel.getDataSetList());
}
}
}
/**
* Calculates the data sets for the specified {@link Stat}.
*
* @param stat stat to calculate the data sets for
*/
private void calculateDataSets(final Stat stat) {
// Data points for each data set, inside being mapped from loop to value.
final Map<LineChartDataSet, Map<Integer, Int>> dataSetPointsMap = new HashMap<>();
final boolean mergeMinGas = stat.hasMinGas && !separateMinsGasCheckBox.isSelected();
final String[] eventFields; // Event fields to query eventually
if (stat.hasMinGas) {
final boolean includeMins = minsCheckBox.isSelected();
final boolean includeGas = gasCheckBox.isSelected();
if (includeMins && includeGas) eventFields = stat.eventFields;
else if (includeMins) eventFields = new String[] {stat.eventFields[0]};
else if (includeGas) eventFields = new String[] {stat.eventFields[1]};
else eventFields = new String[0];
} else eventFields = stat.eventFields;
// Calculate data points maps
for (final Event event : repProc.replay.trackerEvents.events) {
if (event.id != ITrackerEvents.ID_PLAYER_STATS) continue;
final DataModel<LineChartDataSet> model = modelByPlayerIds[event.getPlayerId()];
if (model == null) continue;
// One extra player stat event is recorded when a user leaves (at the same loop) even if at
// the same loop there was a
// scheduled player stat event. So we have to exclude the last player stat event (to avoid the
// chart getting
// "screwed"). (This for example contains mineralsCurrent = 0.)
// Note: if there's a scheduled stat event when the player left, this will be excluded
// wrongly,
// but I don't care, it won't make any noticable difference...
if (event.loop == repProc.usersByPlayerId[event.getPlayerId()].leaveLoop) continue;
// Data sets per event fields
for (int i = 0; i < eventFields.length; i++) {
final String field = eventFields[i];
final LineChartDataSet dataSet = model.getDataSetList().get(mergeMinGas ? 0 : i);
Map<Integer, Int> pointsMap = dataSetPointsMap.get(dataSet);
if (pointsMap == null) dataSetPointsMap.put(dataSet, pointsMap = new HashMap<>());
final Integer loop = Integer.valueOf(event.loop);
Int point = pointsMap.get(loop);
if (point == null) {
pointsMap.put(loop, point = new Int());
}
int value = ((PlayerStatsEvent) event).stats.<Integer>get(field);
if (field == PlayerStatsEvent.F_FOOD_MADE || field == PlayerStatsEvent.F_FOOD_USED)
value >>= 12;
point.value += value;
}
}
// Convert data points maps to arrays
for (final Chart<LineChartDataSet> chart : chartList) {
for (final DataModel<LineChartDataSet> model : chart.getDataModelList()) {
for (final LineChartDataSet dataSet : model.getDataSetList()) {
final Map<Integer, Int> pointsMap = dataSetPointsMap.get(dataSet);
if (pointsMap == null) continue;
// Data points are needed sorted by loop
final List<Entry<Integer, Int>> dataPointList = new ArrayList<>(pointsMap.entrySet());
Collections.sort(
dataPointList,
new Comparator<Entry<Integer, Int>>() {
@Override
public int compare(Entry<Integer, Int> o1, Entry<Integer, Int> o2) {
return o1.getKey().compareTo(o2.getKey());
}
});
int i = 0;
final int[] loops = new int[pointsMap.size()];
final int[] values = new int[pointsMap.size()];
for (final Entry<Integer, Int> dataPoint : dataPointList) {
loops[i] = dataPoint.getKey();
values[i] = dataPoint.getValue().value;
i++;
}
dataSet.setLoops(loops);
dataSet.setValues(values);
dataSet.calculateValueMax();
}
}
}
}
/** Calculates the Spending Quotient data sets. */
private void calculateSQDataSets() {
// Spending Quotient is a function of 2 other Stats: SQ = f( RES_CURRENT, RES_COLL_RATE )
// First calculate RES_CURRENT data set...
calculateDataSets(Stat.RES_CURRENT);
// ...and clone it because we'll need it in a moment
final List<Chart<LineChartDataSet>> clonedChartList = new ArrayList<>(chartList.size());
for (final Chart<LineChartDataSet> chart : chartList) {
final Chart<LineChartDataSet> clonedChart = createChart();
for (final DataModel<LineChartDataSet> model : chart.getDataModelList()) {
final DataModel<LineChartDataSet> clonedModel = new DataModel<>(null, null);
for (final LineChartDataSet dataSet : model.getDataSetList())
clonedModel.addDataSet(
new LineChartDataSet(null, null, dataSet.getLoops(), dataSet.getValues()));
clonedChart.addModel(clonedModel);
}
clonedChartList.add(clonedChart);
}
// Cloning done, let's roll on to calculating the RES_COLL_RATE data set...
calculateDataSets(Stat.RES_COLL_RATE);
// We'll need the last command game event loops indexed by data model (last cmd loop is the same
// for all data sets in a
// model)
final Map<DataModel<LineChartDataSet>, Int> modelLastCmdLoopsMap = new HashMap<>();
for (final Event event : repProc.replay.gameEvents.events) {
if (event.id != IGameEvents.ID_CMD) continue;
// Player stats go by tracker events which go by player id. First check if there is player for
// the user!
final int playerId = repProc.usersByUserId[event.userId].playerId;
if (playerId <= 0) continue;
final DataModel<LineChartDataSet> model = modelByPlayerIds[playerId];
if (model == null) continue;
// Update last command loop per model
Int lastCmdLoop = modelLastCmdLoopsMap.get(model);
if (lastCmdLoop == null) modelLastCmdLoopsMap.put(model, lastCmdLoop = new Int());
lastCmdLoop.value = event.loop;
}
// And the final step: "merge" the 2 data sets, the result being the SQ
for (int chartIdx = 0; chartIdx < chartList.size(); chartIdx++) {
final Chart<LineChartDataSet> chart = chartList.get(chartIdx);
final Chart<LineChartDataSet> clonedChart = clonedChartList.get(chartIdx);
for (int modelIdx = 0; modelIdx < chart.getDataModelList().size(); modelIdx++) {
final DataModel<LineChartDataSet> model = chart.getDataModelList().get(modelIdx);
final DataModel<LineChartDataSet> clonedModel =
clonedChart.getDataModelList().get(modelIdx);
final int lastCmdLoop =
modelLastCmdLoopsMap.get(model) == null ? 0 : modelLastCmdLoopsMap.get(model).value;
for (int dataSetIdx = 0; dataSetIdx < model.getDataSetList().size(); dataSetIdx++) {
final LineChartDataSet dataSet = model.getDataSetList().get(dataSetIdx);
final LineChartDataSet clonedDataSet = clonedModel.getDataSetList().get(dataSetIdx);
// Only include values in total before the last command loop! And of course only count
// samples up to that.
final int[] loops = dataSet.getLoops();
final int[] values = dataSet.getValues();
final int[] clonedValues = clonedDataSet.getValues();
long totalValues = 0, totalClonedValues = 0;
int totalCount = 0;
for (int valueIdx = 0; valueIdx < values.length; valueIdx++) {
if (loops[valueIdx] <= lastCmdLoop) {
totalClonedValues += clonedValues[valueIdx];
totalValues += values[valueIdx];
totalCount++;
}
values[valueIdx] =
RepProcessor.calculateSQImpl(clonedValues[valueIdx], values[valueIdx]);
}
// Calculate average SQ for the data set, put in data set title!
final int avgSQ =
totalCount == 0
? 0
: RepProcessor.calculateSQImpl(
(int) (totalClonedValues / totalCount), (int) (totalValues / totalCount));
dataSet.setTitle("SQ: " + avgSQ);
dataSet.calculateValueMax();
}
}
}
}